R Notebook

Importing the libraries

library(ggplot2)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

records creation

name    = c("Prashanth", "Sam", "Rohan", "Daniel", "Siraj", "Dhoni", "Yuvraj", "Rohith")
age     = c(20, 15, 30, 40, 30, 25, 43, 37)
weight  = c(57, 69, 75, 70, 83, 53, 83, 90)
height  = c(177, 163, 163, 183, 164, 190, 179, 182)
branch = c("Data Analytics", "Machine Learning Engineer", "Data Analytics", "Data Analytics", "Machine Learning Engineer",
           "Business Intelligence Engineer", "Data warehousing Engineer", "Business Intelligence Engineer")
address = c("Chennai", "Madurai", "Punjab", "Salem", "Madurai", "Punjab", "Chennai", "Salem")
score   = c(80, 90, 75, 60, 80, 95, 99, 56)

data-frame creation

df = data.frame (row.names = name, age, weight, height, branch, address, score)
head(df)

Bar Plot

bar_plot = ggplot(data=df, aes(x = branch, y = ..count.. / sum(..count..),fill = factor(branch))) + 
           geom_bar(color='black') +
           labs(y = "Percentage of Branches chosen", title  = "Percentage of the quality of the Branch") +
           scale_y_continuous(labels = scales::percent) +
           coord_flip()

ggplotly(bar_plot)

Histogram

histogram_plot = ggplot(data=df, aes(x=weight)) + 
                 geom_histogram(color = "black",fill = "grey") +
                 labs(x = "Total Weight", y="Count", title="Count of Total Time asleep per day(h)") +
                 scale_x_discrete(labels =labs)

ggplotly(histogram_plot)

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Kernel Density Plot

density_plot = ggplot(data=df, aes(x = height)) +
               geom_density(fill = "indianred3") + 
               labs(x = "height", y="density", title="Kernal density of the height")

ggplotly(density_plot)

Scatter plot

t <- list(family = "Helvetica",size = 14,color = "blue")
t1 <- list(family = "Times New Roman",color = "red")
t2 <- list(family = "Courier New",size = 14,color = "green")
t3 <- list(family = 'Arial')

fig_sp = plot_ly(data = df, x=height, y=weight, color = ~name,
                  type = 'scatter', mode = 'markers')%>%
                          layout(title= list(text = "Body weight vs Brain weight",font = t1), font=t, 
                          legend = list(title=list(text='Animals',font = t2)), 
                          xaxis  = list(title = list(text ='Brain Weight', font = t3)),
                          yaxis  = list(title = list(text ='Body Weight', font = t3)),
                          plot_bgcolor='#e5ecf6')

fig_sp

Pie-Chart

df_order = data.frame(table(df$address))
print(df_order)

##      Var1 Freq
## 1 Chennai    2
## 2 Madurai    2
## 3  Punjab    2
## 4   Salem    2

fig_order = plot_ly(type='pie', labels=df_order$Var1, values=df_order$Freq, 
                    textinfo='label+percent',insidetextorientation='radial')
fig_order